Methods and Arrangements for CSI Reporting

ABSTRACT

Some embodiments provide a method in a wireless device for reporting channel state information, CSI, for a CSI process. The CSI process corresponds to a reference signal resource and an associated interference measurement resource, IMR. According to the method, the wireless device obtains an interference power adjustment value. The wireless device estimates interference and noise based on the IMR, and on the interference power adjustment value. Furthermore, the wireless device determines channel state information based on an estimated effective channel measured based on the reference signal resource, and on the estimated interference and noise. Finally, the wireless device transmits the channel state information to a network node.

TECHNICAL FIELD

This invention relates to methods and arrangements for reporting channel state information.

BACKGROUND

The 3rd Generation Partnership Project (3GPP) is responsible for the standardization of the Universal Mobile Telecommunication System (UMTS) and Long Term Evolution (LTE). The 3GPP work on LTE is also referred to as Evolved Universal Terrestrial Access Network (E-UTRAN). LTE is a technology for realizing high-speed packet-based communication that can reach high data rates both in the downlink and in the uplink, and is thought of as a next generation mobile communication system relative to UMTS. In order to support high data rates, LTE allows for a system bandwidth of 20 MHz, or up to 100 Hz when carrier aggregation is employed. LTE is also able to operate in different frequency bands and can operate in at least Frequency Division Duplex (FDD) and Time Division Duplex (TDD) modes.

LTE uses orthogonal frequency-division multiplexing (OFDM) in the downlink and discrete-Fourier-transform-spread (DFT-spread) OFDM in the uplink. The basic LTE physical resource can be seen as a time-frequency grid, as illustrated in FIG. 1, where each time-frequency resource element (TFRE) corresponds to one subcarrier during one OFDM symbol interval, on a particular antenna port. There is one resource grid per antenna port. The resource allocation in LTE is described in terms of resource blocks, where a resource block corresponds to one slot in the time domain and 12 contiguous 15 kHz subcarriers in the frequency domain. Two time-consecutive resource blocks represent a resource block pair, which corresponds to the time interval upon which scheduling operates.

An antenna port is a “virtual” antenna, which is defined by an antenna port-specific reference signal (RS). An antenna port is defined such that the channel over which a symbol on the antenna port is conveyed can be inferred from the channel over which another symbol on the same antenna port is conveyed. The signal corresponding to an antenna port may possibly be transmitted by several physical antennas, which may also be geographically distributed. In other words, an antenna port may be transmitted from one or several transmission points. Conversely, one transmission point may transmit one or several antenna ports. Antenna ports may interchangeably be referred to as “RS ports”.

Multi-antenna techniques can significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a multiple-input multiple-output (MIMO) communication channel. Such systems and/or related techniques are commonly referred to as MIMO.

The LTE standard is currently evolving with enhanced MIMO support. A core component in LTE is the support of MIMO antenna deployments and MIMO related techniques. LTE Release 10 and above (also referred to as LTE-Advanced) enables support of eight-layer spatial multiplexing with possibly channel dependent precoding. Such spatial multiplexing is aimed for high data rates in favorable channel conditions. An illustration of precoded spatial multiplexing is provided in FIG. 2.

As seen, the information carrying symbol vector s is multiplied by an N_(T)×r precoder matrix W_(N) _(T) _(×r), which serves to distribute the transmit energy in a subspace of the N_(T) dimensional vector space, where N_(T) corresponds to the number of antenna ports. The r symbols in s each are part of a symbol stream, a so-called layer, and r is referred to as the transmission rank. In this way, spatial multiplexing is achieved since multiple symbols can be transmitted simultaneously over the same TFRE. The number of layers, r, is typically adapted to suit the current channel properties.

Furthermore, the precoder matrix is often selected from a codebook of possible precoder matrices, and typically indicated by means of a precoder matrix indicator (PMI), which for a given rank specifies a unique precoder matrix in the codebook. If the precoder matrix is confined to have orthonormal columns, then the design of the codebook of precoder matrices corresponds to a Grassmannian subspace packing problem.

The received N_(R)×1 vector y_(n) on the data TFRE indexed n is modeled by

y _(n) =H _(n) W _(N) _(T) _(×r) s _(n) +e _(n)   (1)

where e_(n) is a noise plus interference vector modeled as realizations of a random process. The precoder for rank r, W_(N) _(T) _(×r), can be a wideband precoder, which is either constant over frequency, or frequency selective.

The precoder matrix is often chosen to match the characteristics of the N_(R)×N_(T) MIMO channel H, resulting in so-called channel dependent precoding. When based on UE feedback, this is commonly referred to as closed-loop precoding and essentially strives for focusing the transmit energy into a subspace which is strong in the sense of conveying much of the transmitted energy to the UE. In addition, the precoder matrix may also be selected to strive for orthogonalizing the channel, meaning that after proper linear equalization at the UE, the inter-layer interference is reduced.

In closed-loop precoding, the UE transmits, based on channel measurements in the forward link, or downlink, recommendations to the base station, which in LTE is called the evolved NodeB (eNodeB) of a suitable precoder to use. A single precoder that is supposed to cover a large bandwidth (wideband precoding) may be fed back. It may also be beneficial to match the frequency variations of the channel and instead feed back a frequency-selective precoding report, e.g. several precoders, one per subband. This is an example of the more general case of channel state information (CSI) feedback, which also encompasses feeding back other entities than precoders to assist the eNodeB in subsequent transmissions to the UE. Thus, channel state information may include one or more of PMI, channel quality indicators (CQIs) or rank indicator (RI).

Signal and channel quality estimation is a fundamental part of a modern wireless system. Noise and interference estimates are used not only in the demodulator, but are also important quantities when estimating, for example, the channel quality indicator (CQI), which is typically used for link adaptation and scheduling decisions on the eNodeB side.

The term e_(n) in (1) represents noise and interference in a TFRE and is typically characterized in terms of second order statistics such as variance and correlation. The interference can be estimated in several ways including from the cell-specific reference symbols (RS) that are present in the time-frequency grid of LTE. Such RS may correspond to the Rel-8 cell-specific RS, CRS (antenna ports 0-3), which are illustrated in FIG. 3, as well as the new CSI RS available in Rel-10, which will be described in more detail below. CRS are sometimes also referred to as common reference signals.

Estimates of interference and noise can be formed in various ways. Estimates can easily be formed based on TFREs containing cell specific RS since s_(n) and W_(N) _(T) _(×r) are then known and H_(n) is given by the channel estimator. It is further noted that the interference on TFREs with data that is scheduled for the UE in question can also be estimated as soon as the data symbols, s_(n) are detected, since at that moment they can be regarded as known symbols. The latter interference can alternatively also be estimated based on second order statistics of the received signal and the signal intended for the UE of interest, thus possibly avoiding needing to decode the transmission before estimating the interference term. Alternatively the interference can be measured on TFREs where the desired signal is muted, so the received signal corresponds to interference only. This has the advantage that the interference measurement may be more accurate and the UE processing becomes trivial because no decoding or desired signal subtraction need to be performed.

Channel State Information Reference Signal (CSI-RS)

In LTE Release-10, a new reference symbol sequence, the CSI-RS, was introduced for the purpose of estimating channel state information. The CSI-RS provides several advantages over basing the CSI feedback on the cell-specific reference symbols (CRS) which were used for that purpose in previous releases. Firstly, the CSI-RS is not used for demodulation of the data signal, and thus does not require the same density. In other words, the overhead of the CSI-RS is substantially less. Secondly, CSI-RS provides a much more flexible means to configure CSI feedback measurements. For example, which CSI-RS resource to measure on can be configured in a UE specific manner. Moreover, the support of antenna configurations larger than 4 antennas must resort to CSI-RS, since the CRS is only defined for at most 4 antennas.

By measuring on a CSI-RS a UE can estimate the effective channel the CSI-RS is traversing including the radio propagation channel, antenna gains, and any possible antenna virtualizations. A CSI-RS port may be precoded so that it is virtualized over multiple physical antenna ports; that is, the CSI-RS port can be transmitted on multiple physical antenna ports, possibly with different gains and phases. In more mathematical rigor this implies that if a known CSI-RS signal x_(n) is transmitted, a UE can estimate the coupling between the transmitted signal and the received signal, i.e. the effective channel. Hence if no virtualization is performed in the transmission:

y _(n) =H _(n) x _(n) +e _(n)

the UE can measure the effective channel H_(eff)=H_(n). Similarly, if the CSI-RS is virtualized using a precoder W_(N) _(T) _(×r) as

y _(n) =H _(n) W _(n) _(T) _(×r) x _(n) +e _(n)

the UE can estimate the effective channel H_(eff)=H_(n)W_(N) _(T) _(×r).

Related to CSI-RS is the concept of zero-power CSI-RS resources (also known as a muted CSI-RS) that are configured just as regular CSI-RS resources, so that a UE knows that the data transmission is mapped around those resources. The intent of the zero-power CSI-RS resources is to enable the network to mute the transmission on the corresponding resources as to boost the SINR of a corresponding non-zero power CSI-RS, possibly transmitted in a neighbor cell/transmission point. For Rel-11 of LTE, a special zero-power CSI-RS that a UE is mandated to use for measuring interference plus noise is under discussion. As the name indicates, a UE can assume that the TPs of interest are not transmitting on the muted CSI-RS resource and the received power can therefore be used as a measure of the interference plus noise level.

Based on a specified CSI-RS resource and an interference measurement configuration, e.g. a muted CSI-RS resource, the UE can estimate the effective channel and noise plus interference, and consequently also determine which rank, precoder and transport format to recommend that best match the particular channel.

Power Measurement Offset

As mentioned above, in LTE a terminal provides the network with channels state information, by means of recommending a particular transmission for a measured effective channel, for example a combination of PMI, RI, and a CQI. To enable this recommendation the UE needs to know the relative power offset between the reference signals (that are used for measuring the effective channel), and a hypothesized upcoming data transmission. In the following we refer to such a power offset as a power measurement offset (PMO). This power offset is tied to a specific reference signal, for example, it relates to the parameter Pc which is part of the configuration message for setting up a measurement on a CSI-RS, or to the parameter nomPDSCH-RS-EPRE-Offset for CRS.

In practice, CQIs are rarely perfect and substantial errors might be present which means that the estimated channel quality does not correspond to the actual channel quality seen for the link over which the transmission takes place. The eNodeB can to some extent reduce the detrimental effects of erroneous CQI reporting by means of outer-loop adjustment of the CQI values. By monitoring the ACK/NACK signaling of the hybrid ARQ, the eNodeB can detect if the block error rate (BLER), or a related measure, is below or above the target value. Using this information, the eNodeB can decide to use more offensive (or defensive) MCS than recommended by the UE. However, outer loop control is a crude tool for improving link adaptation and the convergence of the loops can be slow.

Also, it is more difficult for the eNodeB to deviate from recommended rank, because the CQI reports relates directly to the rank. A change in rank therefore renders the information provided by the CQI reports difficult or impossible to utilize—that is, the eNodeB would have severe difficulties knowing which MCS to use on the different data streams if the eNodeB would override the rank recommended by the UE.

The network can improve the rank reporting by adjusting a PMO in the UE. For example, if the power measurement offset is decreased (causing the terminal to assume a lower power for the transmitted data channel), the terminal will tend to recommend a lower rank since the “optimal” rank is increasing with SINR.

Coordinated Multipoint Transmission (CoMP)

CoMP transmission and reception refers to a system where the transmission and/or reception at multiple, geographically separated antenna sites is coordinated in order to improve system performance. More specifically, CoMP refers to coordination of antenna arrays that have different geographical coverage areas. In the subsequent discussion we refer to a set of antennas covering essentially the same geographical area in the same manner as a point, or more specifically as a Transmission Point (TP). Thus, a point might correspond to one of the sectors at a site, but it may also correspond to a site having one or more antennas all intending to cover a similar geographical area. Often, different points represent different sites. Antennas correspond to different points when they are sufficiently geographically separated and/or have antenna diagrams pointing in sufficiently different directions. Although the present disclosure focuses mainly on downlink CoMP transmission, it should be appreciated that in general, a transmission point may also function as a reception point. The coordination between points can either be distributed, by means of direct communication between the different sites, or by means of a central coordinating node. A further coordination possibility is a “floating cluster” where each transmission point is connected to, and coordinates, a certain set of neighbors (e.g. two neighbors). A set of points that perform coordinated transmission and/or transmission is referred to as a CoMP coordination cluster, a coordination cluster, or simply as a cluster in the following.

FIG. 5 shows an example wireless network with a CoMP coordination cluster comprising three transmission points, denoted TP1, TP2 and TP3.

CoMP is a tool introduced in LTE to improve the coverage of high data rates, the cell-edge throughput and/or to increase system throughput. In particular, the goal is to distribute the user perceived performance more evenly in the network by taking control of the interference in the system, either by reducing the interference and/or by better prediction of the interference.

CoMP operation targets many different deployments, including coordination between sites and sectors in cellular macro deployments, as well as different configurations of Heterogeneous deployments, where for instance a macro node coordinates the transmission with pico nodes within the macro coverage area.

There are many different CoMP transmission schemes that are considered; for example,

Dynamic Point Blanking where multiple transmission points coordinates the transmission so that neighboring transmission points may mute the transmissions on the time-frequency resources (TFREs) that are allocated to UEs that experience significant interference.

Coordinated Beamforming where the TPs coordinate the transmissions in the spatial domain by beamforming the transmission power in such a way that the interference to UEs served by neighboring TPs are suppressed.

Dynamic Point Selection where the data transmission to a UE may switch dynamically (in time and frequency) between different transmission points, so that the transmission points are fully utilized.

Joint Transmission where the signal to a UE is simultaneously transmitted from multiple TPs on the same time/frequency resource. The aim of joint transmission is to increase the received signal power and/or reduce the received interference, if the cooperating TPs otherwise would serve some other UEs without taking our JT UE into consideration.

CoMP Feedback

A common denominator for the CoMP transmission schemes is that the network needs CSI information not only for the serving TP, but also for the channels linking the neighboring TPs to a terminal. By, for example, configuring a unique CSI-RS resource per TP, a UE can resolve the effective channels for each TP by measurements on the corresponding CSI-RS. Note that the UE is likely unaware of the physical presence of a particular TP, it is only configured to measure on a particular CSI-RS resource, without knowing of any association between the CSI-RS resource and a TP.

A detailed example showing which resource elements within a resource block pair may potentially be occupied by UE-specific RS and CSI-RS is provided in FIG. 4. In this example, the CSI-RS utilizes an orthogonal cover code of length two to overlay two antenna ports on two consecutive REs. As seen, many different CSI-RS patterns are available. For the case of 2 CSI-RS antenna ports, for example, there are 20 different patterns within a subframe. The corresponding number of patterns is 10 and 5 for 4 and 8 CSI-RS antenna ports, respectively.

A CSI-RS resource may be described as the pattern of resource elements on which a particular CSI-RS configuration is transmitted. One way of determining a CSI-RS resource is by a combination of the parameters “resourceConfig”, “subframeConfig”, and “antennaPortsCount”, which may be configured by RRC signaling.

Several different types of CoMP feedback are possible. Most alternatives are based on per CSI-RS resource feedback, possibly with CQI aggregation of multiple CSI-RS resources, and also possibly with some sort of co-phasing information between CSI-RS resources. The following is a non-exhaustive list of relevant alternatives (note that a combination of any of these alternatives is also possible):

Per CSI-RS resource feedback corresponds to separate reporting of channel state information (CSI) for each of a set of CSI-RS resources. Such a CSI report may, for example, comprise one or more of a Precoder Matrix Indicator (PMI), Rank Indicator (RI), and/or Channel Quality Indicator (CQI), which represent a recommended configuration for a hypothetical downlink transmission over the same antennas used for the associated CSI-RS, or the RS used for the channel measurement. More generally, the recommended transmission should be mapped to physical antennas in the same way as the reference symbols used for the CSI channel measurement.

Typically there is a one-to-one mapping between a CSI-RS and a TP, in which case per CSI-RS resource feedback corresponds to per-TP feedback; that is, a separate PMI/RI/CQI is reported for each TP. Note that there could be interdependencies between the CSI reports; for example, they could be constrained to have the same RI. Interdependencies between CSI reports have many advantages, such as; reduced search space when the UE computes feedback, reduced feedback overhead, and in the case of reuse of RI there is a reduced need to perform rank override at the eNodeB.

The considered CSI-RS resources are configured by the eNodeB as the CoMP Measurement Set. In the example shown in FIG. 5, different measurement sets may be configured for wireless devices 540 and 550. For example, the measurement set for wireless device 540 may consist of CSI-RS resources transmitted by TP1 and TP2, since these points may be suitable for transmission to device 540. The measurement set for wireless device 550 may instead be configured to consist of CSI-RS resources transmitted by TP2 and TP3. The wireless devices will report CSI information for the transmission points corresponding to their respective measurement sets, thereby enabling the network to e.g. select the most appropriate transmission point for each device.

Aggregate feedback corresponds to a CSI report for a channel that corresponds to an aggregation of multiple CSI-RS. For example, a joint PMI/RI/CQI can be recommended for a joint transmission over all antennas associated with the multiple CSI-RS.

A joint search may however be too computationally demanding for the UE, and a simplified form of aggregation is to evaluate an aggregate CQI which are combined with per CSI-RS resource PMIs, which should typically all be of the same rank corresponding to the aggregated CQI or CQIs. Such a scheme also has the advantage that the aggregated feedback may share much information with a per CSI-RS resource feedback. This is beneficial, because many CoMP transmission schemes require per CSI-RS resource feedback, and to enable eNodeB flexibility in dynamically selecting CoMP scheme, aggregated feedback would typically be transmitted in parallel with per CSI-RS resource feedback. To support coherent joint transmission, such per CSI-RS resource PMIs can be augmented with co-phasing information enabling the eNodeB to rotate the per CSI-RS resource PMIs so that the signals coherently combine at the receiver.

Interference Measurements for CoMP

For efficient CoMP operation it is equally important to capture appropriate interference assumptions when determining the CSI as it is to capture the appropriate received desired signal.

For the purpose of this disclosure, a CSI process is defined as the reporting process of CSI (e.g., CQI and potentially associated PMI/RI) for a particular effective channel, and an interference measurement resource. Optionally, a CSI process may also be associated with one or more interference emulation configurations, as will be explained below. The effective channel is defined by a reference signal resource comprising one or multiple associated reference sequences. The interference measurement resource is a set of resource elements in which one or more signals that are assumed to be interfering with the desired signal are received. The IMR may correspond to a particular CQI reference resource, e.g. a CRS resource. Alternatively, the IMR may be a resource configured specifically for measuring interference.

In uncoordinated systems the UE can effectively measure the interference observed from all other TPs (or all other cells), which will be the relevant interference level in an upcoming data transmission. Such interference measurements are typically performed by analyzing the residual interference on CRS resources, after the UE subtracts the impact of the CRS signal. In coordinated systems performing CoMP such interference measurements becomes increasingly irrelevant. Most notably, within a coordination cluster an eNodeB can to a large extent control which TPs that interfere a UE in any particular TFRE. Hence, there will be multiple interference hypotheses depending on which TPs are transmitting data to other terminals.

For the purpose of improved interference measurements new functionality is introduced in LTE Release 11, where the agreement is that the network will be able to configure which particular TFREs that is to be used for interference measurements for a particular UE; this is defined as an interference measurement resource (IMR). The network can thus control the interference seen on a IMR, by for example muting all TPs within a coordination cluster on the associated TFREs, in which case the terminal will effectively measure the inter CoMP cluster interference. In the example shown in FIG. 5, this would correspond to muting TP1, TP2 and TP3 in the TFREs associated with the IMR.

Consider for example a dynamic point blanking scheme, where there are at least two relevant interference hypotheses for a particular UE: in one interference hypothesis the UE sees no interference from the coordinated transmission point; and in the other hypothesis the UE sees interference from the neighboring point. To enable the network to effectively determine whether or not a TP should be muted, the network may configure the UE to report two, or generally multiple CSIs corresponding to different interference hypotheses—that is, there can be two CSI processes corresponding to different interference situations. Continuing the example of FIG. 5, assume that the wireless device 550 is configured to measure CSI from TP3. However, TP2 may potentially interfere with a transmission from TP2, depending on how the network schedules the transmission. Thus, the network may configure the device 550 with two CSI processes for TP3 (or, more specifically, for measuring the CSI-RS transmitted by TP3). One CSI process is associated with the interference hypothesis that TP2 is silent, and the other CSI process corresponds to the hypothesis that TP3 is transmitting an interfering signal.

To facilitate such a scheme it has been proposed to configure multiple IMRs, wherein the network is responsible for realizing each relevant interference hypothesis in the corresponding IMR. Hence, by associating a particular IMR with a particular CSI process, relevant CSI information, e.g. CQI, can be made available to the network for effective scheduling. In the example of FIG. 5, the network may, for example, configure one IMR in which only TP2 is transmitting, and another IMR in which TP2 and TP3 are both silent. Each CSI process may then be associated with a different IMR.

Although the possibility of associating a CSI process with one or more IMRs enables the network to obtain a better basis for making link adaptation and scheduling decisions, there is still room for further improvement when determining channel state information. In particular, there is a need for improved mechanisms of estimating interference for a particular CSI process.

SUMMARY

An object of some embodiments is to provide an improved mechanism for CSI reporting. Another object of some embodiments is to enable improved link adaptation.

A further object of some embodiments is to improve the estimation of interference for a CSI process, especially in CoMP scenarios.

Some embodiments provide a method in a wireless device for reporting channel state information, CSI, for a CSI process. The CSI process corresponds to a reference signal resource and an associated interference measurement resource, IMR. According to the method, the wireless device obtainings an interference power adjustment value. The wireless device estimates interference and noise based on the IMR, and on the interference power adjustment value. Furthermore, the wireless device determines channel state information based on an estimated effective channel measured based on the reference signal resource, and on the estimated interference and noise, and finally, the wireless device transmits the channel state information to a network node.

Other embodiments provide a method in a network node for receiving channel state information for a CSI process from a wireless device. The network node is comprised in a cluster for coordinated multipoint transmission. According to the method, the network node transmits an indication to the wireless device of an interference power adjustment value associated with the CSI process. The network node then receives channel state information related to the CSI process from the wireless device.

Yet further embodiments provide a wireless device for reporting channel state information for a CSI process. The wireless device comprises radio circuitry and processing circuitry. The processing circuitry is configured to obtain an interference power adjustment value. The processing circuitry is further configured to estimate interference and noise based on the IMR, and on the interference power adjustment value. Furthermore, the processing circuitry is configured to determine channel state information based on an estimated effective channel measured, via the radio circuitry, based on the reference signal resource, and on the estimated interference and noise, and to transmit, via the radio circuitry, the channel state information to a network node.

Some embodiments provide a network node configured to receive channel state information, CSI, for a CSI process. The network node comprises processing circuitry and is connectable to radio circuitry. The processing circuitry is configured to transmit, to a wireless device and via the radio circuitry, an indication of an interference power adjustment value associated with the CSI process. The processing circuitry is further configured to receive, via the radio circuitry, channel state information related to the CSI process from the wireless device.

Thus, particular embodiments provide a CSI process-specific power measurement offset configuration, which is applied by a wireless device when determining CSI. The power measurement offset compensates for a mismatch between estimated interference and the actual interference which may occur in a downlink transmission, leading to a more accurate CSI determination which enables e.g. improved link adaptation by the network. This in turn translates to increased performance in terms of increased spectral efficiency and reduced retransmissions in the hybrid ARQ.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating the LTE time-frequency resource grid.

FIG. 2 is a schematic block diagram illustrating the transmission structure of the precoded spatial multiplexing mode in LTE.

FIG. 3 is a schematic diagram illustrating cell-specific reference signals.

FIG. 4 is a schematic diagram showing example layouts of reference signals.

FIG. 5 is a schematic diagram illustrating a CoMP coordination cluster in a wireless network.

FIG. 6 is a schematic diagram illustrating a CoMP coordination cluster in a wireless network.

FIG. 7 is a schematic diagram illustrating a CoMP coordination cluster in a wireless network.

FIGS. 8-11 are flow charts illustrating methods according to some embodiments.

FIG. 12 a is a block diagram illustrating a network node according to some embodiments.

FIG. 12 b is a block diagram illustrating details of a network node according to some embodiments.

FIG. 13 a is a block diagram illustrating a wireless device according to some embodiments.

FIG. 13 b is a block diagram illustrating details of a wireless device according to some embodiments.

DETAILED DESCRIPTION

A particular problem affecting interference measurements for CoMP is that, even within a single CoMP coordination cluster, different UEs will be configured for CoMP measurements on different TPs within the cluster; that is, each UE may be configured with a separate CoMP Measurement Set not spanning all nodes in the coordination cluster. Hence, each such UE will see a different set of TPs as residual, or uncoordinated, interference.

In particular for larger CoMP clusters it may become prohibitive to configure a distinct IMR for each such residual interference combination. Hence, for some configurations of the CoMP Measurement Set the UE will measure a residual interference lacking the contribution from one or more interfering TPs, and/or wherein one or more TPs that should not interfere are actually included.

This mismatch between the interference measured for the CSI reporting, and the actual interference seen in a downlink transmission, will deteriorate the link adaptation of the network and degrade the overall performance and spectral efficiency of the network. A particularly challenging problem is when incorrectly measured interference levels causes the UE to report mismatched transmission ranks, which is difficult for the eNodeB to override because of the tight coupling to the CQI(s) and the PMI.

Moreover, the interference level experienced for different CSI reports may be substantially different, which may make it challenging to make a power measurement offset have the desired effect for all different operating points.

Some embodiments address this problem by providing an interference power measurement offset that a UE applies to adjust a measured interference and noise. The adjusted measured interference and noise is used by the UE for determining a CSI report for a CSI process. The adjustment value is determined such that it fully or partially compensates for an incorrectly measured or estimated interference level. In some variants, the interference power measurement offset is CSI-process-specific, whereas in other variants, the offset is IMR-specific.

A benefit of associating a specific interference power measurement offset with an interference measurement is that any anticipated mismatch in the measured interference with respect to the interference level that will be experienced by the UE in a corresponding subsequent downlink transmission may be accounted for at the UE side and thereby avoid incorrect rank reports, etc. Thus, some embodiments allow for correcting mismatches in a measured interference and noise to better correspond to a subsequent data transmission, thereby resolving or alleviating the problem of biased or mismatched CSI reports. This improves the link adaptation and overall performance of the system in terms of throughput and reduced number of retransmissions.

FIG. 5 illustrates an example wireless communications system 500 in which various embodiments of the invention may be implemented. The three transmission points 510, 520 and 530 form a CoMP coordination cluster. In the following, for purposes of illustration and not limitation, it will be assumed that the communications system 500 is an LTE system. Transmission points 510, 520 and 530 are remote radio units (RRU:s), controlled by eNodeB 560. In an alternative scenario (not shown), the transmission points could be controlled by separate eNodeBs. It should be appreciated that, generally speaking, each network node, e.g. eNodeB, may control one or more transmission points, which may either be physically co-located with the network node, or geographically distributed. In the scenario shown in FIG. 5, it is assumed that the transmission points 510, 520 and 530 are connected to eNodeB 560, e.g. by optical cable or a point-to-point microwave connection. In the case where some or all of the transmission point forming the cluster are controlled by different eNodeBs, those eNodeBs would be assumed to be connected with each other e.g. by means of a transport network, to be able to exchange information for possible coordination of transmission and reception.

It should be appreciated that although examples herein refer to an eNodeB for purposes of illustration, the invention applies to any network node. The expression “network node” as used in this disclosure is intended to encompass any radio base station, e.g. an eNodeB, NodeB, Home eNodeB or Home NodeB, or any other type of network node that controls all or part of a CoMP cluster.

The communications system 500 further comprises two wireless devices 540 and 550. Within the context of this disclosure, the term “wireless device” encompasses any type of wireless node which is able to communicate with a network node, such as a base station, or with another wireless device by transmitting and/or receiving wireless signals. Thus, the term “wireless device” encompasses, but is not limited to: a user equipment, a mobile terminal, a stationary or mobile wireless device for machine-to-machine communication, an integrated or embedded wireless card, an externally plugged in wireless card, a dongle etc. The wireless device may also be a network node, e.g. a base station. Throughout this disclosure, whenever the term “user equipment” is used this should not be construed as limiting, but should be understood as encompassing any wireless device as defined above.

As mentioned previously, a model of the received data vector on TFREs carrying data symbols can be written as

y=HW _(N) _(T) _(×r) s+e   (1)

where we now for notational simplicity have omitted the subscript n. For feedback computations, the UE needs to assume a similar model for the reception of a hypothetical transmission. However, the model does not necessarily need to be exactly the same. The UE estimates the channel matrix based on reference signals, e.g., Rel-8 cell specific RS or Rel-10 CSI RS, producing a measurement channel matrix H_(m), and also a corresponding measured interference and noise (i.e., the statistics of e).

In one embodiment, the measured interference and noise is adjusted by means of a multiplicative interference measurement offset α, which is used to form a measurement model for feedback determination as

y=H _(m) W _(n) _(T) _(×r) s+√{square root over (α)}·e   (2)

An interference measurement offset can take on many equivalent forms, including be specified in dB or linear scale, re-parameterized as a power offset instead of a scaling factor, etc.

The inclusion of a has the advantage that any anticipated interference measurement mismatch can be accommodated on the UE side. Note that the effective SINR of (2) can be expressed as

${SINR} = \frac{S}{\alpha \cdot I_{e}}$

where S is a desired signal power and I_(e) is the measured interference and noise power (corresponding to e). The effective SINR is thus directly affected by the interference measurement offset.

Moreover, it is beneficial to have such a parameter being configurable by an eNodeB to make the feedback reporting predictable and letting the eNodeB configure measurement adjustments to alleviate known interference measurement mismatches.

In another embodiment the interference measurement offset is additive. One such embodiment corresponds to

${y = {{H_{m}W_{N_{T} \times r}s} + {\left( {1 + \sqrt{\frac{\alpha}{P_{e\;}}}} \right) \cdot e}}},$

where P_(e) is the total received interfering power. Hence in this case α represents an additional interfering power of α (watts) with the same statistical characteristics as e. Also note that a UE may very well apply constraints on the statistics of e, such as enforcing a diagonal structure of an estimated received interference and noise matrix. In such a case, the same diagonal structure will be applied to the additive power measurement offset.

More generally, some embodiments provide a method in a wireless device for reporting CSI for a CSI process, as will now be described with reference to FIG. 5 and the flowchart of FIG. 8. As mentioned above, the CSI process corresponds to a reference signal resource and an interference measurement resource. The reference signal resource comprises a set of resource elements in which one or more reference signals corresponding to a desired signal are received. “Desired signal” in this context means a signal intended for reception by the wireless device. The interference measurement resource comprises a set of resource elements in which one or more signals assumed to be interfering with the desired signal are received.

In particular embodiments the reference signal resource is a CSI-RS resource. However, the reference signal resource may be any other type of RS resource which may be used to estimate a desired signal, e.g. a CRS resource.

The wireless device obtains 810 an interference power adjustment value. The adjustment value may be obtained from a network node, e.g. a serving eNodeB. Alternatively, an indication of the adjustment value is obtained from the network node, e.g. in the form of an index into a lookup table, and the corresponding adjustment value is retrieved from a storage device, such as from the memory of the wireless device. The adjustment value may be associated with the CSI process, i.e. be CSI-process-specific, or it may be associated with the IMR.

In step 820, the wireless device estimates interference and noise based on the IMR, and on the interference power adjustment value.

As part of this estimation, the wireless device performs a measurement on the IMR corresponding to the CSI process, and the adjustment value is then applied to the measured interference and noise. In some variants, the IMR may be a resource which is specifically configured to measure interference. For example, an IMR may consist of resource elements where all transmission points within the CoMP cluster are silent, enabling the wireless device to measure inter-cluster interference and noise. In other variants, the IMR may be a reference signal resource, e.g. a CRS resource. The wireless device may estimate interference in the CRS resource by analyzing the residual signal after subtracting the decoded CRS signal.

Applying the adjustment value to the measured interference may be done in various different ways depending on the form of the adjustment value. In some variants, the adjustment value is a scaling factor, and the wireless device multiplies the measured interference by the adjustment value. Furthermore, the adjustment value may be specified in dB or in linear scale. In another variant, the interference power adjustment value is an additive interference measurement offset, which may be applied to the measured interference by an additive operation.

The wireless device then determines 830 channel state information based on an estimated effective channel which is measured based on the reference signal resource corresponding to the CSI process, and on the estimated interference and noise. Methods for determining CSI based on a channel estimate and interference are known in the art and will not be described in detail here.

Finally, the wireless device transmits 840 the channel state information to a network node.

The effect of applying the adjustment value to the measured interference is to compensate for an error or mismatch in the measured interference. As has been described above, such errors may result e.g. from measuring on an IMR which does not match the interference hypothesis that the network intended to apply for this CSI process.

In another embodiment the interference measurement offset is additive and spatially uncorrelated. One such embodiment corresponds to

y=H _(m) W _(N) _(T) _(×r) s+e+√{square root over (α)}·{tilde over (e)},

where {tilde over (e)} is a random process emulating spatially uncorrelated noise plus interference contribution in addition to the interference process that the UE assumes based on measurements. In one such embodiment the random process is characterized as

${\overset{\sim}{e} \in {{CN}\left( {0,{\frac{{Tr}\left\{ Q_{e} \right\}}{N_{R}} \cdot I_{N_{R}}}} \right)}},$

where Q_(e) is the covariance matrix that is used to govern the second order statistics of the e process. The advantage of this embodiment is that it is not always so that the spatial characteristic of the measured interference plus noise matches the spatial characteristic of the actual interference plus noise at the time of transmission. For instance, if there is an additional source of interference present during transmission compared to what was measured then the spatial properties of this additional source of interference is unknown. Modeling this interference term as spatially uncorrelated is a robust solution.

A method in a wireless device for reporting CSI for a CSI process according to some embodiments, in a scenario where the wireless device emulates spatially uncorrelated interference, will now be described with reference to FIG. 5 and the flowchart of FIG. 9. The CSI process corresponds to a reference signal resource and an interference measurement resource, where the reference signal resource and IMR are defined as described in connection with FIG. 8 above. The CSI process further corresponds to one or more interference emulation configurations. Each interference emulation configuration is associated with a reference signal received from an assumed interferer.

In particular variants, the reference signal resource is a CSI-RS resource. However, as mentioned above, the reference signal resource may be any other type of RS resource which may be used to estimate a desired signal, e.g. a CRS resource.

In step 910, corresponding to 810 above, the wireless device obtains an interference power adjustment value. The same variations as for step 810 apply.

The wireless device then emulates spatially uncorrelated interference for each interference emulation configuration in step 912. Ways of emulating spatially uncorrelated interference have been described above. In one particular embodiment, the wireless device receives information enabling the wireless device to determine a receive covariance matrix.

In a particular variant, the information comprises an indication of which IMR to base the covariance matrix on, e.g. what IMR to measure on to obtain an estimate of the covariance matrix. Thus, instead of measuring an interference power, the wireless device measures an interference covariance matrix based on the IMR.

In another variant, the information comprises an indication to use an identity matrix scaled with the interference power adjustment value.

The covariance matrix may be determined in a variety of ways. For example, the covariance matrix may be diagonal. In a further example, if the interference power adjustment value is an additive interfering power level parameter, the covariance matrix may be determined such that the sum of its diagonal elements is determined by the adjustment value. In yet another example, the receive covariance matrix is determined to be proportional to a measured interference and noise covariance matrix. Yet further, the receive covariance matrix is a scaled identity matrix. In another example, the covariance matrix is diagonal and proportional to the diagonal elements of a measured interference and noise covariance matrix. In yet another example, the covariance matrix is diagonal and proportional to the diagonal elements of a measured received signal covariance matrix.

In step 920, the wireless device estimates interference and noise based on the IMR, on the interference power adjustment value, and on the emulated interference. As part of this estimation, the wireless device performs a measurement on the IMR corresponding to the CSI process, and the adjustment value is then applied to the measured interference and noise. Applying the adjustment value to the measured interference may be done in various different ways, as has already been described above in connection with step 820. The emulated interference is then added to the adjusted measured interference.

The wireless device then determines 930 channel state information, in the same way as for step 830 above.

Finally, the wireless device transmits 840 the channel state information to a network node.

In a particular variant of this embodiment, shown in FIG. 10, the interference power adjustment value is applied to the emulated interference, e.g. by multiplying the emulated interference with the adjustment value (step 1030). The adjusted emulated interference is then added to the adjusted measured interference and noise.

In another embodiment, a CSI process involves recommending CSI for a hypothetical channel wherein the UE emulates interference from an interferer, as outlined above, as

=H _(m) W _(N) _(T) _(×r) s+H _(eff) q _(n) +√{square root over (α)}·e   (3)

where α is a measured interference and noise offset, wherein the interference measurement offset only affects the measured interference and noise part, and not the emulated interference. This has the advantage that an accurate emulated interference level, is not impacted by an interference measurement offset used to correct incorrect interference measurements. Alternatively the interference measurement offset can be applied also to the emulated interference as

y=H _(m) W _(N) _(T) _(×r) s+√{square root over (α)}H _(eff) q _(n) +√{square root over (α)}√e

Thus, this embodiment corresponds to the one described in connection with FIG. 9 20 above, and the corresponding steps and variations apply. However, in this example, the emulated interference and noise is not necessarily spatially uncorrelated but is instead determined based on a channel estimate for each assumed interferer.

In all of the above embodiments, the interference measurement offset may, as a variant, be separately configurable for each of multiple CSI processes. This is useful in that the interference mismatch correction can be optimized for each CSI process, for example each CSI process may involve measurement of different interference levels (e.g., different interference measurement resources).

As another alternative, applicable to all the above embodiments, the interference power adjustment value is IMR-specific. In some scenarios there may be multiple interference measurement resources, each corresponding to a particular interference and noise composition. Each CQI process may be configured—or there may be a standardized contract—to utilize a specific of said IMRs. For this scenario, there may be a benefit to tie a specific interference measurement offset to each of the configured IMRs, as opposed to each of the configured CSI processes.

FIG. 11 a illustrates a method in a network node for receiving CSI information for a CSI process from a wireless device according to some embodiments. This method corresponds to the wireless device methods shown in FIGS. 8-10. The network node is comprised in or controls a cluster for coordinated multipoint transmission, e.g. the cluster TP1-TP3 shown in FIG. 5. More generally, the network node is associated with the cluster. As a particular example, the network node may be the eNodeB 560 controlling TP1-TP3, which are remote radio heads. In an alternative scenario, such as that shown in FIG. 6, the network node is an eNodeB with three sector antennas which correspond to transmission points TP1-TP3. In yet another scenario, as shown in FIG. 7, TP1-TP3 may form a CoMP cluster and the network node may either be the eNodeB controlling TP1 and TP3, or the eNodeB controlling TP2, and serving pico cell 720.

As mentioned above, the CSI process corresponds to a reference signal resource and an interference measurement resource, and optionally also one or more interference emulation configurations.

In optional step 1120, the network node determines an interference power adjustment value based on an interference hypothesis associated with the CSI process. The interference hypothesis corresponding to a set of transmission points assumed to be interfering with a signal intended for reception by the wireless device.

The interference power adjustment value may, for example, be determined such that it compensates for interference from an assumed interfering transmission point according to the interference hypothesis, which interference will not be estimated by the wireless device. In a specific example, the interference power adjustment value is determined based on hybrid-ARQ feedback from the wireless device, as will be further explained below.

The network node further transmits configuration information for the CSI process to the wireless device in step 1110.

In step 1130, the network node transmits an indication to the wireless device of an interference power adjustment value. In one variant, the adjustment value is CSI process-specific, and the indication of the interference power adjustment value is comprised in the CSI process configuration information.

Subsequently, the network node receives 1140 channel state information related to the CSI process from the wireless device.

Optionally, the network node performs 1150 link adaptation and/or scheduling based on the received channel state information.

Some particular methods for determining the adjustment value will now be described. A CSI process-specific interference power adjustment parameter may, for example, be determined by the eNodeB by monitoring the hybrid-ARQ feedback from the UE: If the fraction of the received hybrid-ARQ messages that are associated with transport blocks transmitted according to a recommendation of a particular CSI process corresponds to a NACK (e.g., not successfully decoded by the UE) exceeds (or is below) a target threshold, the adjustment value of that CSI Process can be configured more conservatively (or aggressively) as to better meet the target threshold. Such procedures are often collectively referred to as outer loop link adaptation (OLLA), where the above procedure corresponds to a CSI Process specific OLLA, and where the network configures the OLLA adjustment to be performed by the UE by means of the interference power adjustment parameter (as opposed to having eNodeB side compensation, where the reported CQIs are adjusted by the eNodeB when selecting a transport format for a downlink transmission).

In an alternative/complementary implementation, the eNodeB also utilize hybrid-ARQ messages transmitted by other UEs that are configured with a similar CSI Process, which could speed up the convergence of the CSI Process specific OLLA.

In yet another such implementation, the eNodeB utilizes information specific to the deployment that results in predictable biases in the CSI reporting, such as predictable underestimation of the interference levels for specific CSI processes caused by, for example, interfering transmission points that are muted on an associated interference measurement resource.

FIGS. 12-13 illustrate devices configured to execute the methods described in FIGS. 8-11.

FIG. 12 a illustrates a network node 1200 for receiving, from a wireless device 1300, channel state information, CSI, for a CSI process. The network node 1200 comprises processing circuitry 1220, and is connectable to radio circuitry 1210. In some variants, the radio circuitry 1210 is comprised in the network node 1200, whereas in other variants, the radio circuitry 1210 is external. For example, in the example scenario in FIG. 5, the network node 560 corresponds to network node 1200. The radio circuitry in this example resides in the distributed transmission points TP1-TP3, which are not physically co-located with network node 560. However, in the example shown in FIG. 6, the transmission points correspond to sector antennas at the network node, e.g. the eNodeB, and in this case the radio circuitry may be comprised in the network node.

The processing circuitry 1220 is configured to transmit, via the radio circuitry 1210, an indication of an interference power adjustment value to the wireless device 1300, and to receive, via the radio circuitry 1210, channel state information related to the CSI process from the wireless device 1300.

The processing circuitry 1220 may additionally be configured to perform any of the steps described above as performed by the network node, in particular the steps of FIGS. 11 a-11 b.

FIG. 12 a illustrates details of a possible implementation of processing circuitry 1220.

FIG. 13 a shows a wireless device 1300 for reporting channel state information, CSI, for a CSI process. The wireless device comprises radio circuitry 1310 and processing circuitry 1320.) The processing circuitry 1320 is configured to obtain an interference power adjustment value, and to estimate interference and noise based on the IMR, and on the interference power adjustment value. The processing circuitry 1320 is further configured to determine channel state information based on an estimated effective channel measured, via the radio circuitry 1310, based on the reference signal resource, and on the estimated interference and noise. The processing circuitry 1320 is further configured to transmit, via the radio circuitry 1310, the channel state information to a network node.

The processing circuitry 1320 may additionally be configured to perform any of the steps described above as performed by the wireless device, in particular the steps of FIGS. 8-10.

FIG. 13 b illustrates details of a possible implementation of processing circuitry 1320.

The processing circuitry 1220, 1320 may comprise one or several microprocessors 1630, digital signal processors, and the like, as well as other digital hardware and a memory. The memory, which may comprise one or several types of memory such as read-only memory (ROM), random-access memory, cache memory, flash memory devices, optical storage devices, etc., stores program code for executing one or more telecommunications and/or data communications protocols and for carrying out one or more of the techniques described herein. The memory further stores program data and user data received from the wireless device.

Not all of the steps of the techniques described herein are necessarily performed in a single microprocessor or even in a single module.

It should be noted that although terminology from 3GPP LTE has been used in this disclosure to exemplify the invention, this should not be seen as limiting the scope of the invention to only the aforementioned system. Other wireless systems, including WCDMA, WiMax, UMB and GSM, may also benefit from exploiting the ideas covered within this disclosure.

When using the word “comprise” or “comprising” it shall be interpreted as non-limiting, i.e. meaning “consist at least of”.

The present invention is not limited to the above-describe preferred embodiments. Various alternatives, modifications and equivalents may be used. Therefore, the above embodiments should not be taken as limiting the scope of the invention, which is defined by the appended claims. 

1. A method in a wireless device for reporting channel state information, CSI, for a CSI process, the CSI process corresponding to a reference signal resource and an associated interference measurement resource, IMR, the method characterized in: obtaining an interference power adjustment value; estimating interference and noise based on the IMR, and on the interference power adjustment value; determining channel state information based on an estimated effective channel measured based on the reference signal resource, and on the estimated interference and noise; and transmitting the channel state information to a network node.
 2. The method of claim 1, further comprising applying the interference power adjustment value to interference and noise measured based on the IMR by performing an additive operation in linear scale.
 3. The method of claim 1, further comprising multiplying, in linear scale, the interference power adjustment value with interference and noise measured based on the IMR.
 4. The method of claim 1, wherein the CSI process further corresponds to one or more interference emulation configurations, wherein each interference emulation configuration is associated with a reference signal received from an assumed interferer, the method further comprising: emulating interference for each interference emulation configuration; and estimating interference and noise based also on the emulated interference.
 5. The method of claim 4, wherein emulating interference comprises: estimating, for each interference emulation configuration, an effective channel based on the associated reference signal, and emulating an interfering signal for each interference emulation configuration based on the estimated effective channel for that configuration; and adding the emulated interfering signals to the estimated interference and noise.
 6. The method of claim 4, wherein emulating interference comprises emulating spatially uncorrelated noise and interference.
 7. The method of claim 6, further comprising: receiving information enabling the wireless device to determine a receive covariance matrix; adding an emulated interfering signal corresponding to the receive covariance matrix to the estimated interference and noise.
 8. The method of claim 7, wherein the receive covariance matrix is determined based on the interference power adjustment value.
 9. The method of claim 7, wherein the receive covariance matrix is determined based on a measured interference and noise covariance matrix and/or a measured receive signal covariance matrix.
 10. The method of claim 4, further comprising multiplying, in linear scale, one or more of the emulated interfering signals with the interference power adjustment value.
 11. The method of claim 1, wherein the interference power adjustment value is associated with the CSI process.
 12. The method of claim 1, wherein the interference power adjustment value is associated with the interference measurement resource.
 13. The method of claim 1, wherein the interference power adjustment value is obtained from a network node.
 14. The method of claim 1, further comprising receiving an index from a network node, and obtaining the interference power adjustment value based on the index from a predefined lookup table.
 15. The method of claim 1, wherein the channel state information comprises one or more of: a channel quality indicator, a precoding matrix indicator, a rank indication, and a precoding matrix type.
 16. The method of claim 1, wherein the reference signal resource comprises a set of resource elements in which one or more reference signals corresponding to a desired signal are received, and wherein the interference measurement resource comprises a set of resource elements in which one or more signals assumed to be interfering with the desired signal are received.
 17. A method in a network node for receiving, from a wireless device, channel state information, CSI, for a CSI process, the CSI process corresponding to a reference signal resource and an interference measurement resource, the network node being comprised in a cluster for coordinated multipoint transmission, the method characterized in: transmitting, to the wireless device, an indication of an interference power adjustment value associated with the CSI process; receiving channel state information related to the CSI process from the wireless device.
 18. The method of claim 17, wherein the reference signal resource comprises a set of resource elements in which one or more reference signals corresponding to a signal intended for reception by the wireless device are transmitted, and wherein the interference measurement resource comprises a set of resource elements in which one or more signals assumed to be interfering with the desired signal are received.
 19. The method of claim 17, further comprising determining the interference power adjustment value based on hybrid-ARQ feedback from the wireless device.
 20. The method of claim 17, further comprising determining the interference power adjustment value based on an interference hypothesis associated with the CSI process, the interference hypothesis corresponding to a set of transmission points assumed to be interfering with a signal intended for reception by the wireless device.
 21. The method of claim 17, wherein the interference power adjustment value is determined such that it compensates for interference from an assumed interfering transmission point according to the interference hypothesis, which interference will not be estimated by the wireless device.
 22. The method of claim 17, wherein the interference power adjustment value compensates for interference from one or more transmission points that are assumed to be interfering according to the interference hypothesis, but are not comprised in the measurement set for the wireless device.
 23. The method of claim 17, further comprising: transmitting configuration information for the CSI process to the wireless device.
 24. The method of claim 23, wherein the indication of the interference power adjustment value is comprised in the configuration information.
 25. The method of claim 17, further comprising performing (1150) link adaptation based on the received channel state information.
 26. A wireless device for reporting channel state information, CSI, for a CSI process, the CSI process corresponding to a reference signal resource and an associated interference measurement resource, IMR, the wireless device comprising radio circuitry and processing circuitry, the processing circuitry being configured to: obtain an interference power adjustment value; estimate interference and noise based on the IMR, and on the interference power adjustment value; determine channel state information based on an estimated effective channel measured, via the radio circuitry, based on the reference signal resource, and on the estimated interference and noise; and transmit, via the radio circuitry, the channel state information to a network node.
 27. A network node configured to receive channel state information, CSI, for a CSI process, the CSI process corresponding to a reference signal resource and an interference measurement resource, the network node comprising processing circuitry and being connectable to radio circuitry, wherein the processing circuitry is configured to: transmit, to a wireless device and via the radio circuitry, an indication of an interference power adjustment value associated with the CSI process; receive, via the radio circuitry, channel state information related to the CSI process from the wireless device. 